OpenRaiser/Intern-Atlas huggingface dataset:
Dynamic Rate Allocation in Fading Multiple-access Channels
Venue: arXiv cs.IT 2008
Year: 2008

We consider the problem of rate allocation in a fading Gaussian multiple-access channel (MAC) with fixed transmission powers. Our goal is to maximize a general concave utility function of transmission rates over the throughput capacity region. In contrast to earlier works in this context that propose solutions where a potentially complex optimization problem must be solved in every decision instant, we propose a low-complexity approximate rate allocation policy and analyze the effect of temporal channel variations on its utility performance. To the best of our knowledge, this is the first work that studies the tracking capabilities of an approximate rate allocation scheme under fading channel conditions. We build on an earlier work to present a new rate allocation policy for a fading MAC that implements a low-complexity approximate gradient projection iteration for each channel measurement, and explicitly characterize the effect of the speed of temporal channel variations on the tracking neighborhood of our policy. We further improve our results by proposing an alternative rate allocation policy for which tighter bounds on the size of the tracking neighborhood are derived. These proposed rate allocation policies are computationally efficient in our setting since they implement a single gradient projection iteration per channel measurement and each such iteration relies on approximate projections which has polynomial-complexity in the number of users.
The meaning of concurrent programs
Venue: arXiv cs.DM 2008
Year: 2008

The semantics of assignment and mutual exclusion in concurrent and multi-core/multi-processor systems is presented with attention to low level architectural features in an attempt to make the presentation realistic. Recursive functions on event sequences are used to define state dependent functions and variables in ordinary (non-formal-method) algebra.
Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters
Venue: arXiv cs.DS 2008
Year: 2008

A large body of work has been devoted to defining and identifying clusters or communities in social and information networks. We explore from a novel perspective several questions related to identifying meaningful communities in large social and information networks, and we come to several striking conclusions. We employ approximation algorithms for the graph partitioning problem to characterize as a function of size the statistical and structural properties of partitions of graphs that could plausibly be interpreted as communities. In particular, we define the network community profile plot, which characterizes the "best" possible community--according to the conductance measure--over a wide range of size scales. We study over 100 large real-world social and information networks. Our results suggest a significantly more refined picture of community structure in large networks than has been appreciated previously. In particular, we observe tight communities that are barely connected to the rest of the network at very small size scales; and communities of larger size scales gradually "blend into" the expander-like core of the network and thus become less "community-like." This behavior is not explained, even at a qualitative level, by any of the commonly-used network generation models. Moreover, it is exactly the opposite of what one would expect based on intuition from expander graphs, low-dimensional or manifold-like graphs, and from small social networks that have served as testbeds of community detection algorithms. We have found that a generative graph model, in which new edges are added via an iterative "forest fire" burning process, is able to produce graphs exhibiting a network community profile plot similar to what we observe in our network datasets.
Blind Cognitive MAC Protocols
Venue: arXiv cs.NI 2008
Year: 2008

We consider the design of cognitive Medium Access Control (MAC) protocols enabling an unlicensed (secondary) transmitter-receiver pair to communicate over the idle periods of a set of licensed channels, i.e., the primary network. The objective is to maximize data throughput while maintaining the synchronization between secondary users and avoiding interference with licensed (primary) users. No statistical information about the primary traffic is assumed to be available a-priori to the secondary user. We investigate two distinct sensing scenarios. In the first, the secondary transmitter is capable of sensing all the primary channels, whereas it senses one channel only in the second scenario. In both cases, we propose MAC protocols that efficiently learn the statistics of the primary traffic online. Our simulation results demonstrate that the proposed blind protocols asymptotically achieve the throughput obtained when prior knowledge of primary traffic statistics is available.
On the Utility of Anonymized Flow Traces for Anomaly Detection
Venue: arXiv cs.NI 2008
Year: 2008

The sharing of network traces is an important prerequisite for the development and evaluation of efficient anomaly detection mechanisms. Unfortunately, privacy concerns and data protection laws prevent network operators from sharing these data. Anonymization is a promising solution in this context; however, it is unclear if the sanitization of data preserves the traffic characteristics or introduces artifacts that may falsify traffic analysis results. In this paper, we examine the utility of anonymized flow traces for anomaly detection. We quantitatively evaluate the impact of IP address anonymization, namely variations of permutation and truncation, on the detectability of large-scale anomalies. Specifically, we analyze three weeks of un-sampled and non-anonymized network traces from a medium-sized backbone network. We find that all anonymization techniques, except prefix-preserving permutation, degrade the utility of data for anomaly detection. We show that the degree of degradation depends to a large extent on the nature and mix of anomalies present in a trace. Moreover, we present a case study that illustrates how traffic characteristics of individual hosts are distorted by anonymization.
Visualization Optimization : Application to the RoboCup Rescue Domain
Venue: arXiv cs.GR 2008
Year: 2008

In this paper we demonstrate the use of intelligent optimization methodologies on the visualization optimization of virtual / simulated environments. The problem of automatic selection of an optimized set of views, which better describes an on-going simulation over a virtual environment is addressed in the context of the RoboCup Rescue Simulation domain. A generic architecture for optimization is proposed and described. We outline the possible extensions of this architecture and argue on how several problems within the fields of Interactive Rendering and Visualization can benefit from it.
Modeling of Social Transitions Using Intelligent Systems
Venue: arXiv cs.AI 2008
Year: 2008

In this study, we reproduce two new hybrid intelligent systems, involve three prominent intelligent computing and approximate reasoning methods: Self Organizing feature Map (SOM), Neruo-Fuzzy Inference System and Rough Set Theory (RST),called SONFIS and SORST. We show how our algorithms can be construed as a linkage of government-society interactions, where government catches various states of behaviors: solid (absolute) or flexible. So, transition of society, by changing of connectivity parameters (noise) from order to disorder is inferred.
Enabling Lock-Free Concurrent Fine-Grain Access to Massive Distributed Data: Application to Supernovae Detection
Venue: arXiv cs.DC 2008
Year: 2008

We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and accessed by concurrent clients. On each individual access, a segment of a string, of the order of Megabytes, is read or modified. Our goal is to provide the clients with efficient fine-grain access the data string as concurrently as possible, without locking the string itself. This issue is crucial in the context of applications in the field of astronomy, databases, data mining and multimedia. We illustrate these requiremens with the case of an application for searching supernovae. Our solution relies on distributed, RAM-based data storage, while leveraging a DHT-based, parallel metadata management scheme. The proposed architecture and algorithms have been validated through a software prototype and evaluated in a cluster environment.
A comparison of the notions of optimality in soft constraints and graphical games
Venue: arXiv cs.AI 2008
Year: 2008

The notion of optimality naturally arises in many areas of applied mathematics and computer science concerned with decision making. Here we consider this notion in the context of two formalisms used for different purposes and in different research areas: graphical games and soft constraints. We relate the notion of optimality used in the area of soft constraint satisfaction problems (SCSPs) to that used in graphical games, showing that for a large class of SCSPs that includes weighted constraints every optimal solution corresponds to a Nash equilibrium that is also a Pareto efficient joint strategy.
Optimal Strategies in Sequential Bidding
Venue: arXiv cs.GT 2008
Year: 2008

We are interested in mechanisms that maximize social welfare. In [1] this problem was studied for multi-unit auctions with unit demand bidders and for the public project problem, and in each case social welfare undominated mechanisms in the class of feasible and incentive compatible mechanisms were identified. One way to improve upon these optimality results is by allowing the players to move sequentially. With this in mind, we study here sequential versions of two feasible Groves mechanisms used for single item auctions: the Vickrey auction and the Bailey-Cavallo mechanism. Because of the absence of dominant strategies in this sequential setting, we focus on a weaker concept of an optimal strategy. For each mechanism we introduce natural optimal strategies and observe that in each mechanism these strategies exhibit different behaviour. However, we then show that among all optimal strategies, the one we introduce for each mechanism maximizes the social welfare when each player follows it. The resulting social welfare can be larger than the one obtained in the simultaneous setting. Finally, we show that, when interpreting both mechanisms as simultaneous ones, the vectors of the proposed strategies form a Pareto optimal Nash equilibrium in the class of optimal strategies.
A cache-friendly truncated FFT
Venue: arXiv cs.SC 2008
Year: 2008

We describe a cache-friendly version of van der Hoeven's truncated FFT and inverse truncated FFT, focusing on the case of `large' coefficients, such as those arising in the Schonhage--Strassen algorithm for multiplication in Z[x]. We describe two implementations and examine their performance.
Approximating the Gaussian Multiple Description Rate Region Under Symmetric Distortion Constraints
Venue: arXiv cs.IT 2008
Year: 2008

We consider multiple description coding for the Gaussian source with K descriptions under the symmetric mean squared error distortion constraints, and provide an approximate characterization of the rate region. We show that the rate region can be sandwiched between two polytopes, between which the gap can be upper bounded by constants dependent on the number of descriptions, but independent of the exact distortion constraints. Underlying this result is an exact characterization of the lossless multi-level diversity source coding problem: a lossless counterpart of the MD problem. This connection provides a polytopic template for the inner and outer bounds to the rate region. In order to establish the outer bound, we generalize Ozarow's technique to introduce a strategic expansion of the original probability space by more than one random variables. For the symmetric rate case with any number of descriptions, we show that the gap between the upper bound and the lower bound for the individual description rate is no larger than 0.92 bit. The results developed in this work also suggest the "separation" approach of combining successive refinement quantization and lossless multi-level diversity coding is a competitive one, since it is only a constant away from the optimum. The results are further extended to general sources under the mean squared error distortion measure, where a similar but looser bound on the gap holds.
Design of a Fractional Order PID Controller Using Particle Swarm Optimization Technique
Venue: arXiv cs.OH 2008
Year: 2008

Particle Swarm Optimization technique offers optimal or suboptimal solution to multidimensional rough objective functions. In this paper, this optimization technique is used for designing fractional order PID controllers that give better performance than their integer order counterparts. Controller synthesis is based on required peak overshoot and rise time specifications. The characteristic equation is minimized to obtain an optimum set of controller parameters. Results show that this design method can effectively tune the parameters of the fractional order controller.
On the Capacity and Diversity-Multiplexing Tradeoff of the Two-Way Relay Channel
Venue: arXiv cs.IT 2008
Year: 2008

This paper considers a multiple input multiple output (MIMO) two-way relay channel, where two nodes want to exchange data with each other using multiple relays. An iterative algorithm is proposed to achieve the optimal achievable rate region, when each relay employs an amplify and forward (AF) strategy. The iterative algorithm solves a power minimization problem at every step, subject to minimum signal-to-interference-and-noise ratio constraints, which is non-convex, however, for which the Karush Kuhn Tuker conditions are sufficient for optimality. The optimal AF strategy assumes global channel state information (CSI) at each relay. To simplify the CSI requirements, a simple amplify and forward strategy, called dual channel matching, is also proposed, that requires only local channel state information, and whose achievable rate region is close to that of the optimal AF strategy. In the asymptotic regime of large number of relays, we show that the achievable rate region of the dual channel matching and an upper bound differ by only a constant term and establish the capacity scaling law of the two-way relay channel. Relay strategies achieving optimal diversity-multiplexing tradeoff are also considered with a single relay node. A compress and forward strategy is shown to be optimal for achieving diversity multiplexing tradeoff for the full-duplex case, in general, and for the half-duplex case in some cases.
Entropy of Hidden Markov Processes via Cycle Expansion
Venue: arXiv cs.IT 2008
Year: 2008

Hidden Markov Processes (HMP) is one of the basic tools of the modern probabilistic modeling. The characterization of their entropy remains however an open problem. Here the entropy of HMP is calculated via the cycle expansion of the zeta-function, a method adopted from the theory of dynamical systems. For a class of HMP this method produces exact results both for the entropy and the moment-generating function. The latter allows to estimate, via the Chernoff bound, the probabilities of large deviations for the HMP. More generally, the method offers a representation of the moment-generating function and of the entropy via convergent series.
A constructive proof of the Lovasz Local Lemma
Venue: arXiv cs.DS 2008
Year: 2008

The Lovasz Local Lemma [EL75] is a powerful tool to prove the existence of combinatorial objects meeting a prescribed collection of criteria. The technique can directly be applied to the satisfiability problem, yielding that a k-CNF formula in which each clause has common variables with at most 2^(k-2) other clauses is always satisfiable. All hitherto known proofs of the Local Lemma are non-constructive and do thus not provide a recipe as to how a satisfying assignment to such a formula can be efficiently found. In his breakthrough paper [Bec91], Beck demonstrated that if the neighbourhood of each clause be restricted to O(2^(k/48)), a polynomial time algorithm for the search problem exists. Alon simplified and randomized his procedure and improved the bound to O(2^(k/8)) [Alo91]. Srinivasan presented in [Sri08] a variant that achieves a bound of essentially O(2^(k/4)). In [Mos08], we improved this to O(2^(k/2)). In the present paper, we give a randomized algorithm that finds a satisfying assignment to every k-CNF formula in which each clause has a neighbourhood of at most the asymptotic optimum of 2^(k-5)-1 other clauses and that runs in expected time polynomial in the size of the formula, irrespective of k. If k is considered a constant, we can also give a deterministic variant. In contrast to all previous approaches, our analysis does not anymore invoke the standard non-constructive versions of the Local Lemma and can therefore be considered an alternative, constructive proof of it.
The adaptability of physiological systems optimizes performance: new directions in augmentation
Venue: arXiv cs.HC 2008
Year: 2008

This paper contributes to the human-machine interface community in two ways: as a critique of the closed-loop AC (augmented cognition) approach, and as a way to introduce concepts from complex systems and systems physiology into the field. Of particular relevance is a comparison of the inverted-U (or Gaussian) model of optimal performance and multidimensional fitness landscape model. Hypothetical examples will be given from human physiology and learning and memory. In particular, a four-step model will be introduced that is proposed as a better means to characterize multivariate systems during behavioral processes with complex dynamics such as learning. Finally, the alternate approach presented herein is considered as a preferable design alternate in human-machine systems. It is within this context that future directions are discussed.
On Finite Bases for Weak Semantics: Failures versus Impossible Futures
Venue: arXiv cs.LO 2008
Year: 2008

We provide a finite basis for the (in)equational theory of the process algebra BCCS modulo the weak failures preorder and equivalence. We also give positive and negative results regarding the axiomatizability of BCCS modulo weak impossible futures semantics.
Reliability Bounds for Delay-Constrained Multi-hop Networks
Venue: arXiv cs.IT 2008
Year: 2008

We consider a linear multi-hop network composed of multi-state discrete-time memoryless channels over each hop, with orthogonal time-sharing across hops under a half-duplex relaying protocol. We analyze the probability of error and associated reliability function \cite{Gallager68} over the multi-hop network; with emphasis on random coding and sphere packing bounds, under the assumption of point-to-point coding over each hop. In particular, we define the system reliability function for the multi-hop network and derive lower and upper bounds on this function to specify the reliability-optimal operating conditions of the network under an end-to-end constraint on the total number of channel uses. Moreover, we apply the reliability analysis to bound the expected end-to-end latency of multi-hop communication under the support of an automatic repeat request (ARQ) protocol. Considering an additive white Gaussian noise (AWGN) channel model over each hop, we evaluate and compare these bounds to draw insights on the role of multi-hopping toward enhancing the end-to-end rate-reliability-delay tradeoff.
Lower bounds for distributed markov chain problems
Venue: arXiv cs.DS 2008
Year: 2008

We study the worst-case communication complexity of distributed algorithms computing a path problem based on stationary distributions of random walks in a network $G$ with the caveat that $G$ is also the communication network. The problem is a natural generalization of shortest path lengths to expected path lengths, and represents a model used in many practical applications such as pagerank and eigentrust as well as other problems involving Markov chains defined by networks. For the problem of computing a single stationary probability, we prove an $Ω(n^2 \log n)$ bits lower bound; the trivial centralized algorithm costs $O(n^3)$ bits and no known algorithm beats this. We also prove lower bounds for the related problems of approximately computing the stationary probabilities, computing only the ranking of the nodes, and computing the node with maximal rank. As a corollary, we obtain lower bounds for labelling schemes for the hitting time between two nodes.
Worst-case time decremental connectivity and k-edge witness
Venue: arXiv cs.DS 2008
Year: 2008

We give a simple algorithm for decremental graph connectivity that handles edge deletions in worst-case time $O(k \log n)$ and connectivity queries in $O(\log k)$, where $k$ is the number of edges deleted so far, and uses worst-case space $O(m^2)$. We use this to give an algorithm for $k$-edge witness (``does the removal of a given set of $k$ edges disconnect two vertices $u,v$?'') with worst-case time $O(k^2 \log n)$ and space $O(k^2 n^2)$. For $k = o(\sqrt{n})$ these improve the worst-case $O(\sqrt{n})$ bound for deletion due to Eppstein et al. We also give a decremental connectivity algorithm using $O(n^2 \log n / \log \log n)$ space, whose time complexity depends on the toughness and independence number of the input graph. Finally, we show how to construct a distributed data structure for \kvw by giving a labeling scheme. This is the first data structure for \kvw that can efficiently distributed without just giving each vertex a copy of the whole structure. Its complexity depends on being able to construct a linear layout with good properties.
Programming languages with algorithmically parallelizing problem
Venue: arXiv cs.DC 2008
Year: 2008

The study consists of two parts. Objective of the first part is modern language constructions responsible for algorithmically insolvability of parallelizing problem. Second part contains several ways to modify the constructions to make the problem algorithmically solvable
Automatic Modular Abstractions for Linear Constraints
Venue: arXiv cs.PL 2008
Year: 2008

We propose a method for automatically generating abstract transformers for static analysis by abstract interpretation. The method focuses on linear constraints on programs operating on rational, real or floating-point variables and containing linear assignments and tests. In addition to loop-free code, the same method also applies for obtaining least fixed points as functions of the precondition, which permits the analysis of loops and recursive functions. Our algorithms are based on new quantifier elimination and symbolic manipulation techniques. Given the specification of an abstract domain, and a program block, our method automatically outputs an implementation of the corresponding abstract transformer. It is thus a form of program transformation. The motivation of our work is data-flow synchronous programming languages, used for building control-command embedded systems, but it also applies to imperative and functional programming.
A Bit of Information Theory, and the Data Augmentation Algorithm Converges
Venue: arXiv cs.IT 2008
Year: 2008

The data augmentation (DA) algorithm is a simple and powerful tool in statistical computing. In this note basic information theory is used to prove a nontrivial convergence theorem for the DA algorithm.